Optimisingpurchasing pattern : An optimisation of an order combination and demand forecasting with artificial intelligence

Abstract: The majority of manufacturers provide their customers with volume discounts for placing repeat purchases or placing larger orders. In today's highly competitive market, the topic of how precisely a big number of products should be grouped together naturally emerges.\\In this context, three research questions that were directly relevant to the setting were formulated and their answers were provided. In order to achieve this goal, a number of experiments were carried out. In this particular instance, an algorithm was developed that determines the order combination that is mathematically superior to all others. In this context, an annual order cost saving of 1.33\% could be achieved based on the orders from the year 2021. This could be accomplished without the utilisation of heuristics for a limited number of products at most. In addition, a number of other heuristics have been devised for higher order combination sets. In addition, two other approaches to demand forecasting were investigated, and it was discovered that the time series in this particular instance was insufficient for the application of an RNN-LSTM model.